{"id":"W2392612598","doi":"","title":"A research on relations between urban competitiveness and real estate in Toronto","year":2007,"lang":"en","type":"article","venue":"Urban Problems","topic":"Regional Economic and Spatial Analysis","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Real estate; Real estate development; Economic geography; Business; Estate; Chinese city; Urban planning; Regional science; Corporate Real Estate; Residential real estate; Economy; Geography; China; Finance; Economics; Civil engineering; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002587839,0.0002158119,0.0002028614,0.001326448,0.002012688,0.002657119,0.0003457163,0.0001909686,0.005693703],"category_scores_gemma":[0.001037258,0.0001107893,0.0002752458,0.004102862,0.001746047,0.000899332,0.001021109,0.0003317578,0.0001649838],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01741281,"about_ca_system_score_gemma":0.009845894,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8200215,"about_ca_topic_score_gemma":0.9045229,"domain_scores_codex":[0.9996423,0.00007255917,0.000013823,0.00005058186,0.00009621021,0.0001245528],"domain_scores_gemma":[0.998869,0.0002001747,0.0002481171,0.00002768658,0.0002918247,0.0003630872],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008899037,0.0000435888,0.8857931,0.0001855377,0.0001234772,0.001040386,0.02936898,0.002442284,0.0007083145,0.06040745,0.00412613,0.01567173],"study_design_scores_gemma":[0.000003669923,0.00002846948,0.9262001,0.00006740716,0.00008419309,0.0001158946,0.0563329,0.001224771,0.0002548395,0.001273632,0.01439211,0.00002197179],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9720824,0.0009681922,0.0003407021,0.0008281695,0.00000939993,0.000007776082,0.0003240265,0.00000578663,0.02543357],"genre_scores_gemma":[0.9981325,0.0003440692,0.00006493508,0.00001412241,0.00000297058,0.00000232235,0.00008141237,0.000001459723,0.00135626],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1799785,"threshold_uncertainty_score":0.3620769,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07643573283564238,"score_gpt":0.3011690884896716,"score_spread":0.2247333556540292,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}